「decision」の検索結果

Save durable decisions, findings, plans, and implementation knowledge from the visible pi conversation into a new or existing NeatContext context. Use only when the user explicitly asks to preserve the current conversation as reusable context, or runs /neatcontext-save.

日本語の概要は準備中です。原文の説明を表示しています。

Save durable decisions, findings, plans, and implementation knowledge from the visible Kimi Code conversation into a new or existing NeatContext context. Use only when the user explicitly invokes this skill or asks to preserve the current conversation as reusable context.

日本語の概要は準備中です。原文の説明を表示しています。

Perform a deep architectural analysis or security review requiring extended reasoning. Use for complex architecture decisions, security audits, or when standard analysis is not finding the root cause.

日本語の概要は準備中です。原文の説明を表示しています。

Plan, order and deliver a batch of backlog items (e.g. every High item) in a Conventional Docs repo, one decision, branch, worktree, draft PR, review and merge per item. Use when asked to work through the backlog, implement all items of a priority, or sequence several backlog items end to end.

日本語の概要は準備中です。原文の説明を表示しています。

Build GenAI and agentic apps with genai-tk (tclatos/genai-tk), a YAML-driven IoC toolkit over LangChain, DeepAgents, DeerFlow, and Prefect. Use this skill whenever the user mentions genai-tk, genai_tk, `cli init`, `cli agents run`, `LangchainAgent`, `create_harness`, `get_llm`, `global_config()`, `model_id@provider`, `agents:`/`agent_defaults:` profiles, `RetrieverFactory`, `cli workflow`, or BAML extraction. Also trigger for app_conf.yaml, GENAITK_PROFILE, CodeAct, OpenSandbox, decision models, or "the toolkit".

日本語の概要は準備中です。原文の説明を表示しています。

Plan a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

日本語の概要は準備中です。原文の説明を表示しています。

Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.

日本語の概要は準備中です。原文の説明を表示しています。

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

日本語の概要は準備中です。原文の説明を表示しています。

Review a written plan or design doc through a designer's lens before implementation - seven passes over information architecture, interaction states, emotional arc, AI-slop risk, design-system alignment, responsive and accessibility coverage, and unresolved decisions. Each dimension is rated 0-10 with an explicit statement of what would make it a 10, then the plan is edited to get there. Use when a plan has a UI surface and you want the design gaps closed before code is written. Not for auditing a live site.

日本語の概要は準備中です。原文の説明を表示しています。

Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.

日本語の概要は準備中です。原文の説明を表示しています。

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

日本語の概要は準備中です。原文の説明を表示しています。

Turn a decision you can't fully answer into a questionnaire for someone else to fill in.

日本語の概要は準備中です。原文の説明を表示しています。

Plan a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

日本語の概要は準備中です。原文の説明を表示しています。

Create architecture solution design decisions for AI agent consistency. Use when the user says "lets create architecture" or "create technical architecture" or "create a solution design"

日本語の概要は準備中です。原文の説明を表示しています。

Run the speckit preparation phases end-to-end — specify, plan, critique, tasks — making all decisions autonomously. Stops before implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Run the full speckit workflow end-to-end — specify, plan, critique, tasks, implement, review — making all decisions autonomously. Stops before extract; run that manually.

日本語の概要は準備中です。原文の説明を表示しています。

Read the project's knowledge record before answering from memory or from the files. Use before answering about the project's state, a number, a date, a decision, a source, a deadline or what was agreed - even a casual 'what's the situation with X' or 'is that quote still current'; before changing a recorded value; and whenever the opener or a grounding line names entries. After finding relevant IDs, prefer kpop context to read them with their declared dependencies and checks. Uses pull for concise readings or when the checked reader is unavailable, affects for changed inputs, and search when no ID is known. A missing id is not absence. Not for showing the record's page (the hub skill). Requests come in any language.

日本語の概要は準備中です。原文の説明を表示しています。

Map existing materials into a first knowledge record, or investigate a subject's history in depth. Use whenever the user asks to map, survey, go through, reconstruct or investigate what already exists - folders of documents, decision records, meeting notes, emails, exports, code - or wants a starting record built from existing materials, even when the word 'record' is never said: consult this before listing or reading the files yourself, because a map has an agreed scope, a protocol and a report. Also, once, at a suitable moment, to offer the starting choices where a workspace has no record and the work is clearly ongoing - never on a greeting. Learning while working needs no map. Requests come in any language.

日本語の概要は準備中です。原文の説明を表示しています。

Write what the work found into the project's knowledge record, so the next session inherits it instead of re-deriving it. Use the moment something worth keeping exists: a fact taken from a source, a rule worked out, a decision or conclusion, a measurement, a correction to a recorded value, or a question left open - and check for unrecorded findings before implementation, handoff (including a PR), or finishing work. Record within the user's write authorization. The first write creates GROUNDING.yaml. Covers one-report update, add, set, review, same and distinct, judgments with a falsifier, and background capture.

日本語の概要は準備中です。原文の説明を表示しています。

Jev (TypeSafe System One) inner loop for ego-browser — one ~0.4 s typed decision per DOM step instead of an LLM turn. Use for multi-step clicking through a semantic page: fill known values into a form, set filters, open a row/card/menu by name, reach a page via nav or site search. Escalates login, payment, free text, canvas and content reading back to you.

日本語の概要は準備中です。原文の説明を表示しています。

Builds and improves task-specific decision artifacts from application requirements and labeled records. Use for data assembly, primitive and base-model selection, fitting, export/reload, inference policy, or bounded data/model/program improvement. Includes rules and no-training outcomes; does not require a rung ladder or training a general Jev.

日本語の概要は準備中です。原文の説明を表示しています。

Creates marketing analytics reports, KPI dashboards, ROI calculations, and performance summaries for SME marketing teams. Handles weekly/monthly reporting, campaign analysis, content performance reviews, and data-driven recommendations. Use when user asks about marketing metrics, reporting, KPIs, dashboards, ROI analysis, performance review, or data-driven marketing decisions.

日本語の概要は準備中です。原文の説明を表示しています。

Expert SwiftUI guidance for macOS apps — covers writing and reviewing code with runtime-level understanding of observation, concurrency, performance, and platform integration. Use when user asks to "build a SwiftUI view", "review my SwiftUI code", "fix observation issues", "bridge AppKit", "architect state management", "debug view updates", or works on any macOS SwiftUI project — building features, reviewing existing code, debugging view updates or performance, fixing concurrency issues, architecting state management, bridging AppKit, or making design decisions. Do NOT use for iOS/iPadOS-only SwiftUI, UIKit bridging, or basic Swift language questions. Focuses on non-obvious traps and deep patterns, not basics.

日本語の概要は準備中です。原文の説明を表示しています。

Validate agent output against declared domain rules and ground truth before trusting it downstream. Trigger after any agent produces output that will be used in a decision, stored persistently, or passed to another agent.

日本語の概要は準備中です。原文の説明を表示しています。